10585054 28997 Marc Boel 9967 Supervised Classification 19039 sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder),gradientboostingclassifier=sklearn.ensemble._gb.GradientBoostingClassifier)(2) 8301336 Python_3.7.12. Sklearn_1.0.1. NumPy_1.19.5. SciPy_1.4.1. n_jobs null 19031 remainder "drop" 19031 sparse_threshold 0.3 19031 transformer_weights null 19031 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cont"}}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder", "argument_1": {"oml-python:serialized_object": "function", "value": "openml.extensions.sklearn.cat"}}}] 19031 verbose false 19031 verbose_feature_names_out true 19031 add_indicator false 19032 copy true 19032 fill_value null 19032 missing_values NaN 19032 strategy "most_frequent" 19032 verbose 0 19032 categories "auto" 19033 drop null 19033 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 19033 handle_unknown "ignore" 19033 sparse true 19033 memory null 19039 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "gradientboostingclassifier", "step_name": "gradientboostingclassifier"}}] 19039 verbose false 19039 ccp_alpha 0.0 19040 criterion "friedman_mse" 19040 init null 19040 learning_rate 0.8706146447446743 19040 loss "deviance" 19040 max_depth 3 19040 max_features null 19040 max_leaf_nodes 1726 19040 min_impurity_decrease 0.0 19040 min_samples_leaf 38 19040 min_samples_split 2 19040 min_weight_fraction_leaf 0.0 19040 n_estimators 100 19040 n_iter_no_change 8 19040 random_state 24538 19040 subsample 1.0 19040 tol 0.0001 19040 validation_fraction 0.284245805161085 19040 verbose 0 19040 warm_start false 19040 openml-python Sklearn_1.0.1. 1504 steel-plates-fault https://www.openml.org/data/download/1592296/php9xWOpn -1 22096376 description https://api.openml.org/data/download/22096376/description.xml -1 22096377 predictions https://api.openml.org/data/download/22096377/predictions.arff area_under_roc_curve 0.9987402796462003 [0.99874,0.99874] average_cost 0 f_measure 0.9922839278632269 [0.994064,0.98893] kappa 0.9829943992201314 kb_relative_information_score 0.9747807914817902 mean_absolute_error 0.012133876059558771 mean_prior_absolute_error 0.45306405137877787 weighted_recall 0.9922720247295209 [0.990536,0.995542] number_of_instances 1941 [1268,673] precision 0.9923425616586922 [0.997617,0.982405] predictive_accuracy 0.9922720247295209 prior_entropy 0.9311124141243181 relative_absolute_error 0.026781811584107373 root_mean_prior_squared_error 0.47592842871248736 root_mean_squared_error 0.07858323682665014 root_relative_squared_error 0.16511566043499154 total_cost 0 unweighted_recall 0.9930393126497017 [0.990536,0.995542] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9997649547537901 [0.999765,0.999765] area_under_roc_curve 0.9994123868844753 [0.999412,0.999412] area_under_roc_curve 0.9984722058996357 [0.998472,0.998472] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9996474321306853 [0.999647,0.999647] area_under_roc_curve 1 [1,1] area_under_roc_curve 0.9995299095075801 [0.99953,0.99953] area_under_roc_curve 0.9921802054154994 [0.99218,0.99218] area_under_roc_curve 0.9990662931839402 [0.999066,0.999066] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 1 [1,1] f_measure 0.9948542650470037 [0.996047,0.992593] f_measure 0.9845627951410111 [0.988142,0.977778] f_measure 0.9846129815900818 [0.988048,0.978102] f_measure 1 [1,1] f_measure 0.9845082688528476 [0.988235,0.977444] f_measure 0.9897256153320434 [0.992063,0.985294] f_measure 0.9948542650470037 [0.996047,0.992593] f_measure 0.9948539051709485 [0.996016,0.992701] f_measure 0.9948539051709485 [0.996016,0.992701] kappa 1 kappa 0.9886403560135848 kappa 0.9659210680407543 kappa 0.9661588556808932 kappa 1 kappa 0.965679915084326 kappa 0.9773602520714203 kappa 0.9886403560135848 kappa 0.9887169943003373 kappa 0.9887169943003373 kb_relative_information_score 0.9903497565372484 kb_relative_information_score 0.9789645411347638 kb_relative_information_score 0.965423151997195 kb_relative_information_score 0.9581760441575891 kb_relative_information_score 0.9869736887113961 kb_relative_information_score 0.9668490659800717 kb_relative_information_score 0.963474619572938 kb_relative_information_score 0.9845570594725557 kb_relative_information_score 0.9784254806971094 kb_relative_information_score 0.9744658279588436 mean_absolute_error 0.005033296255428742 mean_absolute_error 0.010473460059424355 mean_absolute_error 0.015131690961165263 mean_absolute_error 0.019950882848380702 mean_absolute_error 0.006445653010195374 mean_absolute_error 0.015359277664387563 mean_absolute_error 0.017876468108256924 mean_absolute_error 0.007359783004294655 mean_absolute_error 0.01081865750365831 mean_absolute_error 0.012926192107221766 mean_prior_absolute_error 0.4536732781714767 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.4526452345453676 mean_prior_absolute_error 0.45422372672718864 mean_prior_absolute_error 0.45422372672718864 number_of_instances 195 [127,68] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [127,67] number_of_instances 194 [126,68] number_of_instances 194 [126,68] precision 1 [1,1] precision 0.9949211643420254 [1,0.985294] precision 0.984646779674069 [0.992063,0.970588] precision 0.98519882179676 [1,0.957143] precision 1 [1,1] precision 0.9845385231177758 [0.984375,0.984848] precision 0.9899895413118183 [1,0.971014] precision 0.9949211643420254 [1,0.985294] precision 0.9949200657403257 [1,0.985507] precision 0.9949200657403257 [1,0.985507] predictive_accuracy 1 predictive_accuracy 0.9948453608247422 predictive_accuracy 0.9845360824742267 predictive_accuracy 0.9845360824742267 predictive_accuracy 1 predictive_accuracy 0.9845360824742267 predictive_accuracy 0.9896907216494846 predictive_accuracy 0.9948453608247422 predictive_accuracy 0.9948453608247422 predictive_accuracy 0.9948453608247422 prior_entropy 0.932928534004902 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9298639109616103 prior_entropy 0.9345694345320188 prior_entropy 0.9345694345320188 relative_absolute_error 0.011094539832090987 relative_absolute_error 0.0231383415975732 relative_absolute_error 0.03342947148524249 relative_absolute_error 0.044076202124206994 relative_absolute_error 0.01423996657485928 relative_absolute_error 0.03393226414901787 relative_absolute_error 0.039493331076846244 relative_absolute_error 0.016259495168852816 relative_absolute_error 0.023817904849686787 relative_absolute_error 0.028457765076163377 root_mean_prior_squared_error 0.4765680392655914 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.47548822532565527 root_mean_prior_squared_error 0.4771452028525092 root_mean_prior_squared_error 0.4771452028525092 root_mean_squared_error 0.03769938953948619 root_mean_squared_error 0.06912085080266055 root_mean_squared_error 0.10177262540250724 root_mean_squared_error 0.1025571129312714 root_mean_squared_error 0.04273953670025383 root_mean_squared_error 0.0822208067926866 root_mean_squared_error 0.08972346866004201 root_mean_squared_error 0.07264703928715614 root_mean_squared_error 0.07849601784107055 root_mean_squared_error 0.0814048215002351 root_relative_squared_error 0.07910599627617143 root_relative_squared_error 0.14536816501674807 root_relative_squared_error 0.2140381611612035 root_relative_squared_error 0.21568801805981938 root_relative_squared_error 0.089885583751274 root_relative_squared_error 0.17291870211165528 root_relative_squared_error 0.1886975615402288 root_relative_squared_error 0.1527840973084059 root_relative_squared_error 0.16451180347575353 root_relative_squared_error 0.1706080685996087 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 unweighted_recall 1 [1,1] unweighted_recall 0.9960629921259843 [0.992126,1] unweighted_recall 0.9846632976848043 [0.984252,0.985075] unweighted_recall 0.9881889763779528 [0.976378,1] unweighted_recall 1 [1,1] unweighted_recall 0.9811376189916559 [0.992126,0.970149] unweighted_recall 0.9921259842519685 [0.984252,1] unweighted_recall 0.9960629921259843 [0.992126,1] unweighted_recall 0.996031746031746 [0.992063,1] unweighted_recall 0.996031746031746 [0.992063,1] usercpu_time_millis 576.5692309978476 usercpu_time_millis 446.60961000045063 usercpu_time_millis 517.3425650009449 usercpu_time_millis 319.5494379997399 usercpu_time_millis 433.20130899883225 usercpu_time_millis 397.21948000078555 usercpu_time_millis 339.1975119993731 usercpu_time_millis 576.4540279997163 usercpu_time_millis 429.68818599911174 usercpu_time_millis 327.8513049990579 usercpu_time_millis_testing 6.899775999045232 usercpu_time_millis_testing 6.289449000178138 usercpu_time_millis_testing 6.924013001480489 usercpu_time_millis_testing 6.614362999243895 usercpu_time_millis_testing 6.66148199888994 usercpu_time_millis_testing 7.179922000432271 usercpu_time_millis_testing 6.4750380006444175 usercpu_time_millis_testing 6.439437000153703 usercpu_time_millis_testing 6.439238999519148 usercpu_time_millis_testing 4.2789489998540375 usercpu_time_millis_training 569.6694549988024 usercpu_time_millis_training 440.3201610002725 usercpu_time_millis_training 510.4185519994644 usercpu_time_millis_training 312.935075000496 usercpu_time_millis_training 426.5398269999423 usercpu_time_millis_training 390.0395580003533 usercpu_time_millis_training 332.7224739987287 usercpu_time_millis_training 570.0145909995626 usercpu_time_millis_training 423.2489469995926 usercpu_time_millis_training 323.57235599920386 wall_clock_time_millis 585.1528644561768 wall_clock_time_millis 449.7549533843994 wall_clock_time_millis 537.6722812652588 wall_clock_time_millis 331.7422866821289 wall_clock_time_millis 445.3320503234863 wall_clock_time_millis 406.97264671325684 wall_clock_time_millis 344.9125289916992 wall_clock_time_millis 596.2982177734375 wall_clock_time_millis 438.24028968811035 wall_clock_time_millis 329.9708366394043 wall_clock_time_millis_testing 6.905078887939453 wall_clock_time_millis_testing 6.296396255493164 wall_clock_time_millis_testing 6.931543350219727 wall_clock_time_millis_testing 12.436628341674805 wall_clock_time_millis_testing 6.667375564575195 wall_clock_time_millis_testing 7.186174392700195 wall_clock_time_millis_testing 6.6089630126953125 wall_clock_time_millis_testing 6.443977355957031 wall_clock_time_millis_testing 8.221626281738281 wall_clock_time_millis_testing 4.283905029296875 wall_clock_time_millis_training 578.2477855682373 wall_clock_time_millis_training 443.45855712890625 wall_clock_time_millis_training 530.7407379150391 wall_clock_time_millis_training 319.3056583404541 wall_clock_time_millis_training 438.66467475891113 wall_clock_time_millis_training 399.78647232055664 wall_clock_time_millis_training 338.3035659790039 wall_clock_time_millis_training 589.8542404174805 wall_clock_time_millis_training 430.01866340637207 wall_clock_time_millis_training 325.6869316101074 weighted_recall 1 [1,1] weighted_recall 0.9948453608247423 [0.992126,1] weighted_recall 0.9845360824742269 [0.984252,0.985075] weighted_recall 0.9845360824742269 [0.976378,1] weighted_recall 1 [1,1] weighted_recall 0.9845360824742269 [0.992126,0.970149] weighted_recall 0.9896907216494846 [0.984252,1] weighted_recall 0.9948453608247423 [0.992126,1] weighted_recall 0.9948453608247423 [0.992063,1] weighted_recall 0.9948453608247423 [0.992063,1]